package com.edu.flink;

import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.TimeCharacteristic;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.util.Collector;

import java.time.Duration;

/**
 * <p>
 *
 * </p>
 *
 * @author jpge
 * @since 2024-04-23
 */
public class DataStreamJob {

    public static void main(String[] args) throws Exception {
        //设置运行时环境
        StreamExecutionEnvironment env =
                StreamExecutionEnvironment.getExecutionEnvironment();

        //设置输入流，并执行数据流的处理和转换
        env.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime);
        DataStream<Tuple2<String, Integer>> dataStream = env
                .socketTextStream("192.168.18.128", 9000)
                .flatMap(new Splitter())
                .keyBy(0)
                .timeWindow(Time.seconds(5))
                .sum(1);
        dataStream.assignTimestampsAndWatermarks(
                WatermarkStrategy.forBoundedOutOfOrderness(Duration.ofSeconds(3))
        );

        //设置输出流
        dataStream.print();
        //执行程序
        env.execute("Window WordCount");
        System.out.print("finished...");
    }

    public static class Splitter implements FlatMapFunction<String, Tuple2<String,
            Integer>> {
        @Override
        public void flatMap(String sentence, Collector<Tuple2<String, Integer>> out)
                throws Exception {
            for (String word : sentence.split(" ")) {
                out.collect(new Tuple2<String, Integer>(word, 1));
            }
        }
    }

}
